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Rhisa

Rhisa specializes in structuring and anonymizing medical datasets to create high-quality, legally compliant data for healthcare research. By utilizing AI methodologies for data enrichment, the company enables faster and more effective medical innovation while ensuring patient privacy.

Paris, FranceFounded 20203500+ followers
Updated 4 months ago

Funding

$410K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

Funding rounds are not available yet.

Founders

Product

Problem

Healthcare research is often hindered by the difficulty of accessing and utilizing medical data due to its unstructured nature, privacy concerns, and legal complexities. Extracting meaningful insights from diverse medical data sources requires significant effort in data preparation, anonymization, and structuring.

Solution

Rhisa provides a platform for structuring, anonymizing, and enriching medical datasets to accelerate healthcare research and innovation. The company leverages AI methodologies to extract and index unstructured data from various medical sources, ensuring the creation of high-quality, legally compliant datasets. By offering representative, multi-source datasets that are fully anonymized, Rhisa enables researchers to train, test, and validate AI algorithms more efficiently while adhering to stringent privacy regulations. The platform facilitates faster data valorization and provides a secure environment for dataset delivery, empowering researchers to extract valuable results with ease.

Target Audience

Rhisa's primary customers are healthcare researchers, AI algorithm developers, and medical institutions seeking high-quality, anonymized medical datasets for research and development purposes.

Features

  • AI-powered data enrichment for extracting and indexing unstructured medical data
  • Anonymization techniques to ensure patient privacy and compliance with regulations like GDPR
  • Data structuration processes to transform raw medical data into usable formats
  • Multi-source data aggregation to reduce biases from hardware or geographical specificities
  • Secure dataset delivery environment for efficient data access and analysis
This profile is AI-generated and may contain inaccuracies.